tbuckley/cabot-search huggingface dataset:
Abstract 727: Detection of early-stage lung cancer using a liquid biopsy test based on extracellular vesicle proteins
Authors: Juan P. Hinestrosa, Jean M. Lewis, Gregor Schroder, Heath I. Balcer, Razelle Kurzrock, Rajaram Krishnan
Journal: Cancer Research (2022)

Abstract We have recently conducted a study to evaluate the use of proteins associated with extracellular vesicles (EVs) isolated using an alternating current electrokinetic (ACE) system for the detection of early stage (I &amp; II) non-small cell lung cancer (NSCLC). Most lung cancers are diagnosed at advanced stages when treatments are less effective, pointing to the need for developing non-invasive screening strategies such as liquid biopsies. We tested the feasibility of detecting the presence of early stage (I-II) lung cancer using protein biomarkers carried by EVs in patient blood. Using an ACE microelectrode array, EVs were purified from NSCLC patient (N = 62; Stage I = 39, Stage II = 23) or control plasma (N = 390) and tested for the presence of cancer biomarker proteins with bead-based multiplex immunoassay kits. A machine learning algorithm based on recursive feature elimination with cross-validation was developed to identify the most important features for differentiation between cases and controls. The algorithm identified 10 protein biomarkers that were able to distinguish between the NSCLC and control patient samples with a receiver-operator characteristic (AUC) of 0.986 (95% CI: 0.976 - 0.996). Sensitivity was 66.1% at 99.2% specificity, rising to 79.0% and 93.6% sensitivity at 98.2% and 95.1% specificity, respectively. When further stratified, Stage I sensitivity was 53.8% and stage II sensitivity was 86.7% at the 99.2% specificity level. These results suggest that it is possible to detect early-stage NSCLC when treatments may be more effective, that EVs may carry the earliest signals of cancer development, and that a test based on blood-based EV-protein biomarkers can yield high sensitivity and specificity. Our results warrant investigation in larger datasets to validate the current observations with the potential application of this methodology for routine screening of at-risk populations. Citation Format: Juan P. Hinestrosa, Jean M. Lewis, Gregor Schroder, Heath I. Balcer, Razelle Kurzrock, Rajaram Krishnan. Detection of early-stage lung cancer using a liquid biopsy test based on extracellular vesicle proteins [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 727.
Abstract 3844: COL11A1: A driver of tumor progression and immune evasion in head and neck squamous cell carcinoma (HNSCC)
Authors: Harmony Ivanna Saunders, Levi Arnold, Mary Markiewicz, Sufi M. Thomas
Journal: Cancer Research (2022)

Abstract We previously reported that collagen type XI alpha 1 (COL11A1) is upregulated in head and neck squamous cell carcinoma (HNSCC) and contributes to tumor progression. Here we tested the hypothesis that COL11A1 regulates the expression of immune regulatory markers in HNSCC. Xena Browser was used to analyze 520 and 42 cancer free normal head and neck tissue samples for COL11A1 expression. The Cancer Genome Atlas (TCGA) RNASeq data from 522 HNSCC samples was downloaded and sorted by clinical parameters and RNA expression for 20,000 genes. COL11A1 expression was correlated with tumor stage (T) and clinical stage (I-IV). Data was sorted by COL11A1 high and low based on the mean COL11A1 expression level and run through the CIBERSORT analysis tool for prediction of immune cell proportions in the tumor. HNSCC lines with COL11A1 knockdown were assessed for immune regulatory markers at the RNA and protein level. COL11A1 was found to be increased in HNSCC relative to normal tissue (tumor vs. normal p&amp;lt;0.0001). COL11A1 expression is highest in HPV negative HNSCC. Its expression correlates with increased tumor (T1 vs T4 p=0.033) and clinical stage (stage III vs. stage IV p=0.023). CIBERSORT analysis demonstrates COL11A1hi patients have significantly decreased active natural killer (NK) cells (active vs. inactive p=0.0166), CD8+ T cells (CD8 low vs. high p&amp;lt;0.0001) and active dendritic cells (active vs. inactive p=0.0035) suggesting immune modulation. COL11A1 targeted lines in vitro show decreased expression of hla-a, -c and cd274 (PD-L1), suggesting COL11A1 expression modulates immune activation by regulating immune suppressive ligands on the tumor cell. COL11A1 is overexpressed in HNSCC and drives tumor proliferation, migration and invasion. Expression levels correlate with tumor and clinical stage. Bioinformatics tool CIBERSORT, predicts decreased immune cell activity in patients with high COL11A1. Targeting COL11A1 in vitro decreased expression of immune suppressive ligands. These preliminary results indicate COL11A1 may drive immune evasion in HPV negative HNSCC. Targeting COL11A1 may improve patient response to immunotherapeutic targets in HNSCC. Citation Format: Harmony Ivanna Saunders, Levi Arnold, Mary Markiewicz, Sufi M. Thomas. COL11A1: A driver of tumor progression and immune evasion in head and neck squamous cell carcinoma (HNSCC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3844.
Abstract 5385: Multiple modes of action of the CD38 x ICAM-1 bispecific antibody
Authors: Xiaocheng Chen, Oi Kwan Wong, Leonard Post
Journal: Cancer Research (2022)

Abstract The cluster of differentiation 38 (CD38) is a well validated target for treating multiple myeloma. Although the anti-CD38 monoclonal antibody treatment has resulted in outstanding responses in patients with multiple myeloma, a significant portion of patients still failed to respond and nearly all patients eventually relapsed. The mechanism of resistance has been partially associated with downregulation of CD38 expression. In addition, CD38 is broadly expressed on normal lymphoid, myeloid, as well as red blood cells (RBCs). To effectively target CD38 on tumor cells, we hypothesize that a bispecific antibody against a tumor associated guide antigen (TAG) and CD38 could achieve tumor specificity and improve potency. ICAM-1, an Ig-like cell adhesion molecule, is highly expressed in multiple myeloma, lymphoma and a subset of solid tumors. Antibody against ICAM-1, bersanlimab (BI505, BioInvent), was well-tolerated, but only showed limited clinical efficacy in MM patients. We generated bispecific CD38 x ICAM-1 antibodies with different formats and geometries and compared their in-vitro activities on ICAM1high tumor cells with low to medium CD38 expression. Our results showed that the asymmetric 1+1 format has potent ADCC and ADCP activities on ICAM-1+CD38medium or ICAM-1+CD38low cells. Fc modifications further improved ADCC activities of the bispecific antibody. To further understand the impact of antigen densities, we tested ADCC activities on a selected set of myeloma and lymphoma cell lines with a range of CD38 and ICAM-1 expressions. We observed superior ADCC activity on cells with extremely low CD38 expression. Moreover, we showed that the bispecific antibody reduced NK fratricide and RBC binding comparing to the bivalent CD38 antibody. Most importantly, the CD38 x ICAM1 bispecific antibody demonstrated potent tumor inhibition activities in in-vivo myeloma and lymphoma models. These studies suggested that CD38 x ICAM-1 bispecific antibody has multiple modes of action for treating lymphoma and multiple myeloma. Citation Format: Xiaocheng Chen, Oi Kwan Wong, Leonard Post. Multiple modes of action of the CD38 x ICAM-1 bispecific antibody [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5385.
Abstract 227: Kethoxal-assisted single-stranded DNA sequencing (KAS-seq) reveals dynamic and temporal changes in transcription in response to UVB exposure
Authors: Emma A. Wilkinson, Tong Wu, Gayoung Park, Yan-Hong Cui, Chuan He, Yu-Ying He
Journal: Cancer Research (2022)

Abstract Skin cancer is the most common form of cancer, with over 5 million cases reported in 2021. UVB exposure derived from sunlight is the major carcinogenic driver of skin cancer and poses a major public health risk. In response to UVB exposure, keratinocytes must activate DNA repair pathways to avoid mutagenesis. In addition to DNA repair pathways, cells initiate well-coordinated DNA damage response pathways to facilitate the repair process, including arresting global transcription. Here we report the use of kethoxal-assisted single-strand DNA-Sequencing (KAS-Seq) technology to profile the transcriptional dynamics that underlie the DNA damage response upon UVB exposure. Mechanistically, KAS-Seq involves the addition of an azide-tagged kethoxal group (N3-kethoxal) to DNA samples, which then reacts with guanines on single-stranded DNA (ssDNA). A “KAS signal” is therefore only obtained when DNA is unwound, allowing the N3-kethoxal reaction with accessible guanines to occur. Accordingly, in response to DNA damage, DNA can form ssDNA bubbles in order to facilitate DNA damage recognition and repair processes. KAS-Seq is therefore a suitable method to profile the transcriptional dynamics that occur in response to UVB-induced DNA damage. Here we show that UVB exposure in normal human keratinocytes (NHEK) cells induces a temporal and dynamic reprogramming in transcription using KAS-Seq. In terms of global transcription, our data show that the greatest loss of KAS signal occurs rapidly between 30mins and 3hrs post-UVB exposure, signifying transcriptional arrest. Interestingly, KAS signal is regained between 6-24hrs post-UVB, which is representative of a transition towards transcriptional recovery and induction of DNA damage processes. Furthermore, a more discrete and targeted analysis shows that the gain and loss of KAS signals primarily occur within the gene body, followed by promoter and intergenic regions. Overall, our data shows that transcriptional control in response to UVB-induced DNA damage is both dynamic and temporal. Further analysis is required to identify which transcriptional phenotype (transcriptional arrest or transcriptional recovery) is the most deleterious to the cell and DNA damage repair processes when disrupted. Additionally, we aim to further elucidate the molecular mechanisms that underlie these global changes in transcription, which will provide expanded insights into the wide-ranging oncogenic mechanisms that underlie UVB exposure. Citation Format: Emma A. Wilkinson, Tong Wu, Gayoung Park, Yan-Hong Cui, Chuan He, Yu-Ying He. Kethoxal-assisted single-stranded DNA sequencing (KAS-seq) reveals dynamic and temporal changes in transcription in response to UVB exposure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 227.
Abstract 2574: Q901; a highly selective covalent cdk7 inhibitor inducing substantial anti-tumor effect in a broad spectrum of solid tumor lineages
Authors: Donghoon Yu, Yeejin Jeon, Seung-Joo Lee, Jaeseung Kim, Kiyean Nam
Journal: Cancer Research (2022)

Abstract As a key regulator of its dual role in transcription and cell cycle progression, CDK7 has been determined to be an attractive therapeutic target in a variety of tumor types driven by cell cycle dysregulation and aberrant control of the transcriptional processes. Q901 is an irreversible small molecule inhibitor with extreme selectivity and potent inhibition activity for CDK7, which forms a covalent bond with C312 of the CDK7 C-terminal domain. Q901 demonstrated selective cytotoxic activities in a broad spectrum of solid tumor lineages. TP53 mutation could be a potential predictive marker for the Q901 response as TP53 wild-type cancer cells demonstrates a significantly increased cytotoxic response compared to TP53 mutant cells in the bioinformatic analysis. In addition, gene expression profiling analysis showed a dose-response increase of POLR2A expression upon Q901 treatment and a correlation with tumor growth inhibition rate, indicating that POLR2A might be a potential PD marker for the Q901-induced response. Taken together, these data support the clinical development of Q901 for solid tumor indications. Q901 is progressing to IND-enabling studies to support the start of Phase 1 oncology clinical trials in early 2022. Citation Format: Donghoon Yu, Yeejin Jeon, Seung-Joo Lee, Jaeseung Kim, Kiyean Nam. Q901; a highly selective covalent cdk7 inhibitor inducing substantial anti-tumor effect in a broad spectrum of solid tumor lineages [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2574.
Abstract 236: Nuclear receptor 4A1 ligands target T-cell exhaustion in colorectal cancer
Authors: Kumaravel Mohankumar, Gus Wright, Subhashree Kumaravel, Rupesh Shrestha, Lei Zhang, Maen Abdelrahim, Robert S. Chapkin, Stephen Safe
Journal: Cancer Research (2022)

Abstract Colorectal cancer (CRC) is a highly complex disease with multiple risk factors. The orphan nuclear receptor 4A1 (NR4A1) is overexpressed in several cancers and is a negative prognostic factor for cancer patient survival. Previous reports indicate a potential role for overexpression of NR4A1 in T-cell exhaustion and in this study, we aim to investigate the antitumorigenic activity of two bis-indole derived ligands (DIMs) that act as receptor antagonists. Immune competent C57BL/6 mice and mouse MC-38 colon cancer cells were used and tumor Infiltrating Lymphocytes (TILs) were isolated from mice either untreated or treated with CDIM/NR4A1 antagonists. FACS analysis and Real -Time PCR were performed to determine expression of exhaustion markers in these tumor T-cell population. 1,1-Bis(3΄-indolyl)-1-(3-bromo-5-trifluoromethoxyphenyl)methane (DIM-3-Br-5-OCF3) and the 3,5-dichlorophenyl analog (DIM-3,5-Cl2) at doses of 2.5 and 7.5 mg/kg/d inhibited tumor growth and downregulated expression of PD-L1, an NR4A1-regulated gene in MC-38 - derived tumors and cells. The mouse MC-38 colon cancer cell line was used in a syngeneic mouse model of colon cancer and tumor infiltrating lymphocytes (TILs) from MC-38 cell-derived colon tumors exhibited multiple markers of T-cell exhaustion in both CD8+ and CD4+ T-cells. Lymphocytes from an enlarged spleen in these tumor-bearing animals also exhibited markers of CD8+ and CD4+ T-cell exhaustion. Analysis of CD8+ cells from TILs showed that treatment with the NR4A1 antagonists modulated expression of several genes associated with T-cell exhaustion namely a decrease in TOX, TOX2 and NFAT mRNAs, activation of T-Bet. The percentage of CD8+ and CD4+ T-cells from tumors and spleen expressing PD-1, 2B4 and TIGIT was decreased in the treated vs control mice and TIM3 expression was also decreased in CD8+ (tumors and spleen) and CD4+ (tumors) T-cells. These findings suggest that NR4A1 antagonists are highly effective as anticancer agents in this mouse syngeneic colon tumor model by inactivating the pro-oncogenic activities of NR4A1 in tumors and by remediating NR4A1-regulated T-cell exhaustion in tumor and splenic lymphocytes. Citation Format: Kumaravel Mohankumar, Gus Wright, Subhashree Kumaravel, Rupesh Shrestha, Lei Zhang, Maen Abdelrahim, Robert S. Chapkin, Stephen Safe. Nuclear receptor 4A1 ligands target T-cell exhaustion in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 236.
Abstract 1944: Prognostic biomarkers for gallbladder cancer: A machine learning approach
Authors: Linsey Jackson, Loretta Allotey, Valles Kenneth, Gavin Oliver, Asha Nair, Daniel O'Brien, Rondell Graham, Mitesh Borad, Arjun Athreya, Lewis Roberts
Journal: Cancer Research (2022)

Abstract Gallbladder cancer (GBC) is one of the deadliest cancers, with a 5-year-survival-rate of less than 5 percent for late-stage disease. The response rate to chemotherapy among GBC patients is generally poor. Recent research has attempted to identify diagnostic, prognostic, and predictive biomarkers, however, currently, no biomarkers can accurately diagnose GBC and predict patients’ prognosis. Integrative analysis of molecular and clinical characterization has not been fully established, and minimal improvement has been made to the survival of these patients, in part due to the heterogeneity of GBC. Machine learning techniques have been proven to empower analysis of big data in oncology, allowing for improvement in the generation of biomarkers to predict patient outcomes. Using machine learning, we can utilize high-throughput RNA sequencing with clinicopathologic data to develop a predictive tool for GBC prognosis. Current predictive models for GBC outcomes often utilize clinical data only, with the highest C-statistic reported being 0.71. C-statistic values over 0.7 generally indicate good models, however 0.8 is the threshold for strong predictive models. We aim to build a superior algorithm to predict overall survival in GBC patients with advanced disease, using machine learning approaches to prioritize biomarkers for GBC prognosis. We have identified over 80 fresh frozen GBC tissue samples from Mayo Clinic Rochester, Dongsan Medical Center in Daegu, Korea, University of the Witwatersrand, in Johannesburg, South Africa, Lithuanian University of Health Science in Vilnius, Lithuania, and University of Calgary in Calgary, Canada, from patients enrolled between 2012 and 2021. We will perform next-generation RNA sequencing on these tissue samples. The patients’ clinical, pathologic and survival data will be abstracted from the medical record uniformly across sites. Feature engineering and dimensionality reduction will be performed. Then random forests, support vector machines, and gradient boosting machines will be applied to train the data. Variable importance will prioritize multi-omic markers. Standard 5-fold cross validation will be used to assess performance of each ML algorithm. If overall survival can be better predicted with the addition patients’ transcriptional sequencing data compared to using clinical profiles alone, we can gain a greater understanding of key biomarkers driving the tumor phenotype. Citation Format: Linsey Jackson, Loretta Allotey, Valles Kenneth, Gavin Oliver, Asha Nair, Daniel O'Brien, Rondell Graham, Mitesh Borad, Arjun Athreya, Lewis Roberts. Prognostic biomarkers for gallbladder cancer: A machine learning approach [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1944.
Abstract 709: Metabolomic differences between pulmonary metastasis of Lewis lung carcinoma and normal lungs from C57BL/6 mice fed an obesogenic high-fat diet
Authors: Lin Yan, Sneha Sundaram, Bret M. Rust, Matthew J. Picklo, Michael R. Bukowski
Journal: Cancer Research (2022)

Abstract Metastasis, the spread of malignant cells from a primary tumor to distant organs, is the most devastating aspect of cancer. To understand the metabolism of metastases, we compared the metabolomes of pulmonary metastases of Lewis lung carcinoma (LLC) with that of normal lung tissues from mice fed an obesogenic high-fat diet. In a 2x2 design, male C57BL/6 mice, with or without a subcutaneous LLC inoculation, were fed the standard AIN93G diet or a high-fat diet (HFD), which provided 16% or 45% of energy from soybean oil, for 12 weeks. At the end of the study, lung metastases from injected mice and the lungs from non-injected mice were harvested for untargeted metabolomic analysis of primary metabolism by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS). We identified 91 metabolites, 70 of which differed among the four groups. Pathway and network analyses along with the discriminant analysis showed that amino acid and carbohydrate metabolism were altered the most in metastases compared to the normal lung tissue (e.g., aminoacyl-tRNA biosynthesis pathways and the citric cycle). A 60% decrease in glutamine and a 25-fold elevation in sorbitol were observed in metastases. Cholesterol and its metabolite dihydrocholesterol were 50% lower in metastases than in the lungs. The HFD elevated arachidonic acid and its precursor linoleic acid in the lungs from non-LLC-bearing mice, which reflected dietary fatty acid composition of the HFD. However, such elevation did not occur in metastases from HFD-fed LLC-bearing mice, suggesting alterations in fatty acid metabolism during LLC metastatic progression. Differences in metabolomes between LLC pulmonary metastases and the normal healthy lungs identified in the present study can be useful in designing targeted studies for prevention and treatment of metastasis using this spontaneous metastasis model. Citation Format: Lin Yan, Sneha Sundaram, Bret M. Rust, Matthew J. Picklo, Michael R. Bukowski. Metabolomic differences between pulmonary metastasis of Lewis lung carcinoma and normal lungs from C57BL/6 mice fed an obesogenic high-fat diet [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 709.
Abstract SY05-02: Applications of base editor technology in small molecule: Target validation
Authors: Audrey Griffith, Annabel Sangree, Priyanka Roy, Ruth Hanna, John Doench
Journal: Cancer Research (2022)

Abstract CRISPR screens that focus on the gene as the unit of information - whether using knockout, interference, or activation - have reinvigorated the field of functional genomics. The recent development of Base Editor technology allows nucleotide-level manipulation, enabling fine-scale investigation of endogenous loci. The low upfront costs of generating a pooled base editing library, coupled with the small scale and relative ease of executing such screens, makes the financial barrier to entry for such experiments low while also not requiring deep experience with screening. One application of this technology is screens that aim to identify resistance mutations in putative targets of small molecules, which provides excellent evidence that the phenotype is caused by on-target activity of the small molecule. This has heretofore typically been an extraordinarily laborious and time-consuming experimental path, by either slowly cultivating spontaneous drug resistant mutants or by generating and screening large scale ORF-variant pools. Base editor screens are well-suited to vastly accelerate this process. Using both A&amp;gt;G and C&amp;gt;T base editors, coupled with variants of the SpCas9 enzyme, we have conducted drug resistance screens with small molecules that target the anti-apoptotic proteins MCL1, BCL2L1, and BCL2, as well as the DNA repair regulator PARP1. These screens identified resistance residues that were also observed in clinical samples, illustrating the utility of this approach. Additionally, base editor screens are excellent tools for studying genetic variants, as we will demonstrate with screens identifying loss-of-function mutations in BRCA1, BRCA2, and TP53. We anticipate that the tools and methodologies described here will facilitate the investigation of impactful variants at a finer and deeper resolution for any locus of interest. Citation Format: Audrey Griffith, Annabel Sangree, Priyanka Roy, Ruth Hanna, John Doench. Applications of base editor technology in small molecule: Target validation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr SY05-02.